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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1990年第1期38卷 23-34页

作者： FISCHER, TR GIBSON, JD KOO, B TEXAS A&M UNIV SYST DEPT ELECT ENGN COLLEGE STN TX 77843 USA

The minimum-mean-squared-error encoding of a noisy source is considered within the context of alphabet-constrained data compression. Just as in the block-coding formulation, the optimum source coder consists of an optimum estimator followed by optimum source coding of the resulting estimates. However, unlike the block approach, the alphabet-constrained viewpoint admits estimators based on the past history of source observations outside the current block of interest. If delayed encoding is allowed, the estimator is an optimum smoother. For Gauss-Markov sources, the encoding performance is characterized in terms of the estimation error covariance, and it is demonstrated that for moderate block sizes, significant reduction in mean-squared error can be achieved compared to the block coder performance. Extensive experiments are reported for vector quantization of noisy speech using the Y.L. Linde, A. Buzo, and R.M. Gray (IEEE Trans. Commun., ***-28, p.84-95, 1980) training mode vector quantizer. The results indicate that the alphabet-constrained estimator, which is a Kalman filter, is superior to the block estimator, and, in particular, that adaptivity is critical for good performance over a variety of speech sources.< >

关键词： source coding Delay estimation Block codes Encoding Speech Data compression History Gaussian processes Acoustic distortion Estimation error

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Second-Order Resolvability, Intrinsic Randomness, and Fixed-Length source coding for Mixed sources: Information Spectrum Approach

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IEEE TRANSACTIONS ON INFORMATION THEORY 2013年第1期59卷 1-16页

作者： Nomura, Ryo Han, Te Sun Senshu Univ Sch Network & Informat Kanagawa Japan Natl Inst Informat & Commun Technol Tokyo Japan

The second-order achievable asymptotics in typical random number generation problems such as resolvability, intrinsic randomness, and fixed-length source coding are considered. In these problems, several researchers have derived the first-order and the second-order achievability rates for general sources using the information spectrum methods. Although these formulas are general, their computations are quite hard. Hence, an attempt to address explicit computation problems of achievable rates is meaningful. In particular, for i.i.d. sources, the second-order achievable rates have earlier been determined simply by using the asymptotic normality. In this paper, we consider mixed sources of two i.i.d. sources. The mixed source is a typical case of non-ergodic sources and whose self-information does not have the asymptotic normality. Nonetheless, we can explicitly compute the second-order achievable rates for these sources on the basis of two-peak asymptotic normality. In addition, extensions of our results to more general mixed sources, such as a mixture of countably infinite i.i.d. sources or Markov sources, and a continuous mixture of i.i.d. sources, are considered.

关键词： Asymptotic normality mixed source random number generation second-order achievability source coding

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Designing routes for source coding with explicit side information in sensor networks

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IEEE-ACM TRANSACTIONS ON NETWORKING 2007年第6期15卷 1401-1413页

作者： Luo, Huiyu Pottie, Gregory J. Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA

In this paper, we study the problem of designing routes for source coding with explicit side information (i.e., with side information at both the encoder and the decoder) in sensor networks. Two difficulties in constructing such data-centric routes are the lack of reasonably practical data aggregation models and the high computational complexity resulting from the coupling of routing and in-network data fusion. Our data aggregation model is built upon the observation that in many physical situations the side information providing the most coding gain comes from a small number of nearby sensors. Based on this model, we formulate an optimization problem to minimize the communication cost, and show that finding the exact solution of this problem is NP-hard. Subsequently, two suboptimal algorithms are proposed. One is inspired by the balanced trees that have small total weights and reasonable distance from each sensor to the fusion center [6]. The other separately routes the explicit side information to achieve cost minimization. Bounds on the worst-case performance ratios of two methods to the optimal solution are derived for a special class of rate models, and simulations are conducted to shed light, on their average behaviors.

关键词： data-centric routing maximum weight branching NP-hardness shortest path tree source coding Steiner tree

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Sequential source coding for Stochastic Systems Subject to Finite Rate Constraints

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2022年第8期67卷 3822-3835页

作者： Stavrou, Photios A. Skoglund, Mikael Tanaka, Takashi KTH Royal Inst Technol Div Informat Sci & Engn S-11428 Stockholm Sweden Univ Austin Dept Aerosp Engn & Engn Mech Austin TX 78712 USA

In this article, we revisit the sequential source-coding framework to analyze fundamental performance limitations of discrete-time stochastic control systems subject to feedback data-rate constraints in finite-time horizon. The basis of our results is a new characterization of the lower bound on the minimum total-rate achieved by sequential codes subject to a total (across time) distortion constraint and a computational algorithm that allocates optimally the rate-distortion, for a given distortion level, at each instant of time and any fixed finite-time horizon. The idea behind this characterization facilitates the derivation of analytical, nonasymptotic, and finite-dimensional lower and upper bounds in two control-related scenarios: a) A parallel time-varying Gauss-Markov process with identically distributed spatial components that are quantized and transmitted through a noiseless channel to a minimum mean-squared error decoder;and b) a time-varying quantized linear quadratic Gaussian (LQG) closed-loop control system, with identically distributed spatial components and with a random data-rate allocation. Our nonasymptotic lower bound on the quantized LQG control problem reveals the absolute minimum data-rates for (mean square) stability of our time-varying plant for any fixed finite-time horizon. We supplement our framework with illustrative simulation experiments.

关键词： Distortion Upper bound source coding Markov processes Heuristic algorithms Resource description framework Rate-distortion Finite-time horizon quantization reverse-waterfilling sequential causal coding stochastic systems

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Goal-Oriented source coding and Filtering for Vehicular Communications

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IEEE INTERNET OF THINGS JOURNAL 2024年第11期11卷 19804-19822页

作者： Gimenez-Guzman, Jose Manuel Leyva-Mayorga, Israel Popovski, Petar Univ Politecn Valencia Dept Commun Valencia 46022 Spain Aalborg Univ Dept Elect Syst DK-9220 Aalborg Denmark

Vehicle-to-everything (V2X) networks will constitute a prominent application in future generations of cellular networks, definitely transforming our conception of transportation systems. A major challenge in V2X networks is the vast amount of data generated by the large number of sensors in the vehicles, which saturates the wireless links. As it is not possible to meet the throughput, timing, and reliability requirements for the total bulk of generated data, one needs to filter out data based on the actual communication goal. In this article, we present an architecture and diverse options to implement filtering and source coding for goal-oriented (GO) vehicular communications. We illustrate how filtering and source coding contribute to meeting the strict delay requirements while maintaining energy-efficient operation. Our results show that GO communications, performed as the combination of Bloom filtering and GO source coding, can greatly contribute not only to reduce the energy consumption by up to 30% but also to decrease delay, which in turn increases the supported amount of delay-sensitive traffic by up to 819.2%.

关键词： Vehicle-to-everything Semantics source coding Sensors Internet of Things Delays 6G mobile communication Bloom filter (BF) discontinuous reception (DRX) goal-oriented (GO) communications intelligent transportation systems (ITSs) source coding vehicle-to-everything (V2X)

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On source coding with side-information-dependent distortion measures

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IEEE TRANSACTIONS ON INFORMATION THEORY 2000年第7期46卷 2697-2704页

作者： Linder, T Zamir, R Zeger, K Queens Univ Dept Math & Stat Kingston ON K7L 3N6 Canada Tel Aviv Univ Dept Elect Engn Syst IL-69978 Ramat Aviv Israel Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA

High-resolution bounds in lossy coding of a real memoryless source are considered when side information is present. Let X be a "smooth" source and let Y be the side information. First we treat the case when both the encoder and the decoder have access to Y and we establish an asymptotically tight thigh-resolution) formula for the conditional rate-distortion function R-X\Y(D) for a class of locally quadratic distortion measures which may be functions of th side information. We then consider the case when only the decoder has access to the side information (i.e., the "Wyner-Ziv problem"). For side-information-dependent distortion measures, we give an explicit formula which tightly approximates the Wyner-Ziv rate-distortion function R-WZ(D) for small D under some assumptions on the joint distribution of X and Y. These results demonstrate that for side-information-dependent distortion measures the rate loss R-WZ(D) - R-X\Y(D) can be bounded away from zero in the limit of small D. This contrasts the case of distortion measures which do not depend on the side information where the rate loss vanishes as D --> 0.

关键词： conditional rate distortion general distortion measures high-resolution theory Shannon lower bound side information source coding Wyner-Ziv problem

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Bucket-Filling: An Asymptotically Optimal Video-on-Demand Network With source coding

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IEEE TRANSACTIONS ON MULTIMEDIA 2015年第5期17卷 723-735页

作者： Chang, Zhangyu Chan, S. -H. Gary Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Hong Kong Hong Kong Peoples R China

There has recently been growing interest for content providers to provide video-on-demand (VoD) as a cloud service. In such a network, the content provider may rent heterogeneous resources (such as streaming and storage capacities) from geographically distributed data centers deployed close to user pools. These data centers (or proxy servers) collaboratively share content with each other to serve their local users. A critical challenge is to optimize movie storage and retrieval to minimize the deployment cost consisting of streaming, storage, and network transmission between data centers. We propose a novel and effective movie storage and retrieval using linear source coding. All the movies are source-encoded once at the repository, by taking every source symbols of movie to generate coded symbols. These coded symbols are then distributed to the servers in the cloud. Based on a general and comprehensive cost model, we optimize and the number of symbols to retrieve from remote servers for a local movie request. The optimal solution can be efficiently computed with a linear programming (LP) formulation. Our solution is proved to asymptotically approach the global minimum cost as increases. Even when is low, near optimality can be achieved. To accommodate large movie pool and system parameter changes, we propose algorithms for movie grouping and on-line re-optimization which significantly reduce the computational complexity with little compromise on optimality. Through extensive simulation, our algorithm is shown to achieve the lowest cost, outperforming traditional and state-of-the-art heuristics with a substantially wide margin.

关键词： Distributed video-on-demand (VoD) cloud linear programming (LP) optimization source coding

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Achievability Performance Bounds for Integer-Forcing source coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2020年第3期66卷 1482-1496页

作者： Domanovitz, Elad Erez, Uri Tel Aviv Univ Dept Elect Engn Syst IL-6997801 Tel Aviv Israel

Integer-forcing source coding has been proposed as a low-complexity method for compression of distributed correlated Gaussian sources. In this scheme, each encoder quantizes its observation using the same fine lattice and reduces the result modulo a coarse lattice. Rather than directly recovering the individual quantized signals, the decoder first recovers a full-rank set of judiciously chosen integer linear combinations of the quantized signals, and then inverts it. It has been observed that the method works very well for "most" but not all source covariance matrices. The present work quantifies the measure of bad covariance matrices by studying the probability that integer-forcing source coding fails as a function of the allocated rate, where the probability is with respect to a random orthonormal transformation that is applied to the sources prior to quantization. For the important case where the signals to be compressed correspond to the antenna inputs of relays in an i.i.d. Rayleigh fading environment, this orthonormal transformation can be viewed as being performed by nature. The scheme is also studied in the context of a non-distributed system. Here, the goal is to arrive at a universal, yet practical, compression method using equal-rate quantizers with provable performance guarantees. The scheme is universal in the sense that the covariance matrix need only be learned at the decoder but not at the encoder. The goal is accomplished by replacing the random orthonormal transformation by transformations corresponding to number-theoretic space-time codes.

关键词： source coding Covariance matrices Precoding Lattices Decoding Quantization (signal) Distortion Distributed compression integer forcing unitary precoding

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Secure Multiterminal source coding With Side Information at the Eavesdropper

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IEEE TRANSACTIONS ON INFORMATION THEORY 2013年第6期59卷 3668-3692页

作者： Villard, Joffrey Piantanida, Pablo SUPELEC Dept Telecommun F-91192 Gif Sur Yvette France

The problem of secure multiterminal source coding with side information at the eavesdropper is investigated. This scenario consists of a main encoder (referred to as Alice) that wishes to compress a single source but simultaneously satisfying the desired requirements on the distortion level at a legitimate receiver (referred to as Bob) and the equivocation rate-average uncertainty-at an eavesdropper (referred to as Eve). It is further assumed the presence of a (public) rate-limited link between Alice and Bob. In this setting, Eve perfectly observes the information bits sent by Alice to Bob and has also access to a correlated source which can be used as side information. A second encoder (referred to as Charlie) helps Bob in estimating Alice's source by sending a compressed version of its own correlated observation via a (private) rate-limited link, which is only observed by Bob. For instance, the problem at hands can be seen as the unification between the Berger-Tung and the secure source coding setups. Inner and outer bounds on the so-called rate-distortion-equivocation region are derived. The inner region turns to be tight for two cases: 1) uncoded side information at Bob and 2) lossless reconstruction of both sources at Bob-secure distributed lossless compression. Application examples to secure lossy source coding of Gaussian and binary sources in the presence of Gaussian and binary/ternary (respectively) side informations are also considered. Optimal coding schemes are characterized for some cases of interest where the statistical differences between the side information at the decoders and the presence of a nonzero distortion at Bob can be fully exploited to guarantee secrecy.

关键词： Distributed source coding eavesdropper equivocation-rate rate-distortion region random codes secrecy source coding side information source coding Wyner-Ziv coding

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Abelian Group Codes for Channel coding and source coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2015年第5期61卷 2399-2414页

作者： Sahebi, Aria Ghasemian Pradhan, S. Sandeep Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA

In this paper, we study the asymptotic performance of Abelian group codes for the channel coding problem for arbitrary discrete (finite alphabet) memoryless channels as well as the lossy source coding problem for arbitrary discrete (finite alphabet) memoryless sources. For the channel coding problem, we find the capacity characterized in a single-letter information-theoretic form. This simplifies to the symmetric capacity of the channel when the underlying group is a field. For the source coding problem, we derive the achievable rate-distortion function that is characterized in a single-letter information-theoretic form. When the underlying group is a field, it simplifies to the symmetric rate-distortion function. We give several illustrative examples. Due to the nonsymmetric nature of the sources and channels considered, our analysis uses a synergy of information-theoretic and group-theoretic tools.

关键词： Group codes group capacity source coding channel coding abelian groups

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